Abstract: The Inhibitory-Spillover-Effect (ISE) on a deception task was investigated. The ISE occurs when performance in one self-control task facilitates performance in another (simultaneously conducted) self-control task. Deceiving requires increased access to inhibitory control. We hypothesized that inducing liars to control urination urgency (physical inhibition) would facilitate control during deceptive interviews (cognitive inhibition). Participants drank small (low-control) or large (high-control) amounts of water. Next, they lied or told the truth to an interviewer. Third-party observers assessed the presence of behavioral cues and made true/lie judgments. In the high-control, but not the low-control condition, liars displayed significantly fewer behavioral cues to deception, more behavioral cues signaling truth, and provided longer and more complex accounts than truth-tellers. Accuracy detecting liars in the high-control condition was significantly impaired; observers revealed bias toward perceiving liars as truth-tellers. The ISE can operate in complex behaviors. Acts of deception can be facilitated by covert manipulations of self-control.

Here’s a hard truth: regardless of the boilerplate in your privacy policy, none of your users have given informed consent to being tracked. Every tracker and beacon script on your web site increases the privacy cost they pay for transacting with you, chipping away at the trust in the relationship.

Because

The all too typical corporate big data strategy boils down to three steps:

Write down all the data

???

Profit

This never makes sense. You can’t expect the value of data to just appear out of thin air. Data isn’t fissile material. It doesn’t spontaneously reach critical mass and start producing insights.

Which leads to the realization:

Think this way for a while, and you notice a key factor: old data usually isn’t very interesting. You’ll be much more interested in what your users are doing right now than what they were doing a year ago. Sure, spotting trends in historical data might be cool, but in all likelihood it isn’t actionable. Today’s data is.

So

Actionable insight is an asset. Data is a liability. And old data is a non-performing loan.